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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. MonetDB vs Vertica

MonetDB vs Vertica

OverviewComparisonAlternatives

Overview

Vertica
Vertica
Stacks88
Followers120
Votes16
MonetDB
MonetDB
Stacks13
Followers35
Votes2

MonetDB vs Vertica: What are the differences?

MonetDB vs Vertica

MonetDB and Vertica are two popular analytical database management systems that are known for their performance and scalability. In this comparison, we will highlight the key differences between MonetDB and Vertica.

1. **Architecture**: MonetDB is an in-memory column-store database that focuses on maximizing query performance by storing data in columns rather than rows. On the other hand, Vertica uses a combination of columnar storage and optimized compression techniques to improve query performance and storage efficiency.

2. **Query Processing**: MonetDB employs a vectorized query processing model, where operations are performed on blocks of data, leading to high query throughput. In contrast, Vertica utilizes a combination of compiled query execution and projection pruning to optimize query processing and improve performance.

3. **Concurrency Control**: MonetDB implements a multi-version concurrency control (MVCC) mechanism to handle concurrent transactions and ensure data consistency. In comparison, Vertica utilizes a hybrid locking mechanism that combines row-level and column-level locks to manage concurrent transactions effectively.

4. **Data Distribution**: MonetDB follows a shared-nothing architecture, where data is partitioned across multiple nodes to enable parallel processing and scalability. In contrast, Vertica employs a distributed architecture that partitions data based on the hashing of a designated key, allowing for efficient data distribution and query execution.

5. **Indexing**: MonetDB uses bitmap indexes and B-trees to optimize query performance by efficiently accessing and retrieving data. On the other hand, Vertica leverages zone maps and projections to speed up query processing and reduce I/O overhead by storing metadata about data distribution and statistics.

6. **Data Loading**: MonetDB offers efficient bulk loading capabilities through its COPY INTO command, allowing users to load large volumes of data quickly. In comparison, Vertica provides high-speed data loading using its native support for parallel data loading and ingestion from various data sources.

In Summary, MonetDB and Vertica differ in their architecture, query processing, concurrency control, data distribution, indexing, and data loading capabilities, making them suitable choices for different use cases based on performance and scalability requirements in analytical database environments.

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Detailed Comparison

Vertica
Vertica
MonetDB
MonetDB

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

MonetDB innovates at all layers of a DBMS, e.g. a storage model based on vertical fragmentation, a modern CPU-tuned query execution architecture, automatic and self-tuning indexes, run-time query optimization, and a modular software architecture.

Analyze All of Your Data. No longer move data or settle for siloed views;Achieve Scale and Performance;Fear of growing data volumes and users is a thing of the past;Future-Proof Your Analytics
-
Statistics
Stacks
88
Stacks
13
Followers
120
Followers
35
Votes
16
Votes
2
Pros & Cons
Pros
  • 3
    Shared nothing or shared everything architecture
  • 1
    Vertica is the only product which offers partition prun
  • 1
    Query-Optimized Storage
  • 1
    Fully automated Database Designer tool
  • 1
    Near-Real-Time Analytics in pure Column Store
Pros
  • 2
    High Performance
Integrations
Oracle
Oracle
Golang
Golang
MongoDB
MongoDB
MySQL
MySQL
Sass
Sass
Mode
Mode
PowerBI
PowerBI
Tableau
Tableau
Talend
Talend
No integrations available

What are some alternatives to Vertica, MonetDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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